Problem-Oriented Automatic Summarization Method with Semantic Coherence Definition and Usage of Inclusion Measures for the Search of Answers to Questions in the Internet

Abstract

The article deals with the relevant problem of automatic arbitrary text summary obtaining. Several works in this field are analyzed using comparison and classification methods. The problem of obtaining a text summary by means of an answer to a random question is emphasized. The identification of semantic relations between sentences using a set of rules based on syntax and semantics of a language is described. These rules are represented in the form of regular expressions – patterns that consist of characters and metacharacters and set search rules. Taking into account semantic coherence features, an improved method of sentences similarity calculation to identify the measure of inclusion of one sentence into another one is developed. This method helps to define more precisely logical stress on the words within automatic summarization and detect contradictions. A modified automatic summarization method, oriented at a specific problem is suggested. It is concluded that the proposed method is quiet effective in the process of automatic search for answers to questions in the Internet.